What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic, and ethical questions and show that GPT-3 is not designed to pass any of them. (...) This is a reminder that GPT-3 does not do what it is not supposed to do, and that any interpretation of GPT-3 as the beginning of the emergence of a general form of artificial intelligence is merely uninformed science fiction. We conclude by outlining some of the significant consequences of the industrialisation of automatic and cheap production of good, semantic artefacts. (shrink)

A line of research within embodied cognition seeks to show that an organism’s body is a determinant of its conceptual capacities. Comparison of this claim of body determinism to linguistic determinism bears interesting results. Just as Slobin’s (1996) idea of thinking for speaking challenges the main thesis of linguistic determinism, so too the possibility of thinking for acting raises difficulties for the proponent of body determinism. However, recent studies suggest that the body may, after all, have a determining role in (...) cognitive processes of sentence comprehension. (shrink)

A phenomenon “emerges” when a concept is instantiated for the first time: hence emergence is relative to a set of concepts. Propositional thought and language emerge together. It is proposed that the degree of complexity of an object language relative to a given metalanguage can be gauged by the number of ways it can be translated into that metalanguage: in analogy with other forms of measurement, the more ways the object language can be translated into the metalanguage, the less powerful (...) the conceptual resources of the object language. (shrink)

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders (...) plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the ‘phyto-nervous’ system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify. (shrink)

The digital is deeply transforming reality. Through discussion of concepts such as identity, location, presence, law and territoriality, this article explores why and how these transformations are occurring, and highlights the importance of having a design and a plan for our new digital world.

This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and (...) hence that none of them provides a valid solution to the SGP, which remains an open problem. (shrink)

This paper explores aspects of GPT-3 that have been discussed as harbingers of artificial general intelligence and, in particular, linguistic intelligence. After introducing key features of GPT-3 and assessing its performance in the light of the conversational standards set by Alan Turing in his seminal paper from 1950, the paper elucidates the difference between clever automation and genuine linguistic intelligence. A central theme of this discussion on genuine conversational intelligence is that members of a linguistic community never merely respond “algorithmically” (...) to queries through a selective kind of pattern recognition, because they must also jointly attend and act with other speakers in order to count as genuinely intelligent and trustworthy. This presents a challenge for systems like GPT-3, because representing the world in a way that makes conversational common ground salient is an essentially collective task that we can only achieve jointly with other speakers. Thus, the main difficulty for any artificially intelligent model of conversation is to account for the communicational intentions and motivations of a speaker through joint attention. These joint motivations and intentions seem to be completely absent from the standard way in which systems like GPT-3 and other artificial intelligent systems work. This is not merely a theoretical issue. Since GPT-3 and future iterations of similar systems will likely be available for commercial use through application programming interfaces, caution is needed regarding the risks created by these systems, which pass for “intelligent” but have no genuine communicational intentions, and can thereby produce fake and unreliable linguistic exchanges. (shrink)

This article contributes to the debate around the abilities of large language models such as GPT-3, dealing with: firstly, evaluating how well GPT does in the Turing Test, secondly the limits of such models, especially their tendency to generate falsehoods, and thirdly the social consequences of the problems these models have with truth-telling. We start by formalising the recently proposed notion of reversible questions, which Floridi & Chiriatti propose allow one to ‘identify the nature of the source of their answers’, (...) as a probabilistic measure based on Item Response Theory from psychometrics. Following a critical assessment of the methodology which led previous scholars to dismiss GPT’s abilities, we argue against claims that GPT-3 completely lacks semantic ability. Using ideas of compression, priming, distributional semantics and semantic webs we offer our own theory of the limits of large language models like GPT-3, and argue that GPT can competently engage in various semantic tasks. The real reason GPT’s answers seem senseless being that truth-telling is not amongst them. We claim that these kinds of models cannot be forced into producing only true continuation, but rather to maximise their objective function they strategize to be plausible instead of truthful. This, we moreover claim, can hijack our intuitive capacity to evaluate the accuracy of its outputs. Finally, we show how this analysis predicts that a widespread adoption of language generators as tools for writing could result in permanent pollution of our informational ecosystem with massive amounts of very plausible but often untrue texts. (shrink)

Discusses the possibility of reconciling different articulations of intentionality from a neurobiological perspective. The author analyzes the relationship between agency and representation and how representation is intrinsically related to action control. The author also presents a new account of action, arguing against what is still commonly held as its proper definition, namely the final outcome of a cascade-like process that starts from the analysis of sensory data, incorporates the result of decision processes, and ends up with responses (actions) to externally-or (...) internally-generated stimuli. The author discusses recent findings from the investigation of neural mechanisms that are at the basis of sensorimotor integration. (shrink)

How does cultural knowledge shape the development of human minds and, conversely, what kind of species-specific social-cognitive mechanisms have evolved to support the intergenerational reproduction of cultural knowledge? We critically examine current theories proposing a human-specific drive to identify with and imitate conspecifics as the evolutionary mechanism underlying cultural learning. We summarize new data demonstrating the selective interpretive nature of imitative learning in 14-month-olds and argue that the predictive scope of existing imitative learning models is either too broad or too (...) narrow to account for these findings. We outline our alternative theory of a human-specific adaptation for ‘pedagogy’, a communicative system of mutual design specialized for the fast and efficient transfer of new and relevant cultural knowledge from knowledgeable to ignorant conspecifics. We show the central role that innately specified ostensive-communicative triggering cues and learner-directed manner of knowledge manifestations play in constraining and guiding selective imitation of relevant cultural knowledge that is both new and cognitively opaque to the naive learner. (shrink)

Artificial agents are progressively becoming more present in everyday-life situations and more sophisticated in their interaction affordances. In some specific cases, like Google Duplex, GPT-3 bots or Deep Mind’s AlphaGo Zero, their capabilities reach or exceed human levels. The use contexts of everyday life necessitate making such agents understandable by laypeople. At the same time, displaying human levels of social behavior has kindled the debate over the adoption of Dennett’s ‘intentional stance’. By means of a comparative analysis of the literature (...) on robots and virtual agents, we defend the thesis that approaching these artificial agents ‘as if’ they had intentions and forms of social, goal-oriented rationality is the only way to deal with their complexity on a daily base. Specifically, we claim that this is the only viable strategy for non-expert users to understand, predict and perhaps learn from artificial agents’ behavior in everyday social contexts. Furthermore, we argue that as long as agents are transparent about their design principles and functionality, attributing intentions to their actions is not only essential, but also ethical. Additionally, we propose design guidelines inspired by the debate over the adoption of the intentional stance. (shrink)

Deep learning techniques have revolutionised artificial systems’ performance on myriad tasks, from playing Go to medical diagnosis. Recent developments have extended such successes to natural language processing, an area once deemed beyond such systems’ reach. Despite their different goals, these successes have suggested that such systems may be pertinent to theoretical linguistics. The competence/performance distinction presents a fundamental barrier to such inferences. While DL systems are trained on linguistic performance, linguistic theories are aimed at competence. Such a barrier has traditionally (...) been sidestepped by assuming a fairly close correspondence: performance as competence plus noise. I argue this assumption is unmotivated. Competence and performance can differ arbitrarily. Thus, we should not expect DL models to illuminate linguistic theory. (shrink)

In 1975, Colwyn Trevarthen first presented his groundbreaking explorations into the early origins of human intersubjectivity. His influential model dictates that, during intimate and playful spontaneous face-to-face protoconversations, the emotions of both the 2–3-month-old infant and mother are nonverbally communicated, perceived, mutually regulated, and intersubjectively shared. This primordial basic interpersonal interaction is expressed in synchronized rhythmic-turn-taking transactions that promote the intercoordination and awareness of positive brain states in both. In this work, I offer an interpersonal neurobiological model of Trevarthen’s intersubjective (...) protoconversations as rapid, reciprocal, bidirectional visual-facial, auditory-prosodic, and tactile-gestural right brain-to-right brain implicit nonverbal communications between the psychobiologically attuned mother and the developing infant. These co-constructed positive emotional interactions facilitate the experience-dependent maturation of the infant’s right brain, which is in an early critical period of growth. I then address the central role of interpersonal synchrony in intersubjectivity, expressed in a mutual alignment or coupling between the minds and bodies of the mother and infant in face-to-face protoconversations, as well as how these right brain-to-right brain emotional transmissions generate bioenergetic positively charged interbrain synchrony within the dyad. Following this, I offer recent brain laterality research on the essential functions of the right temporoparietal junction, a central node of the social brain, in face-to-face nonverbal communications. In the next section, I describe the ongoing development of the protoconversation over the 1st year and beyond, and the co-creation of a fundamental energy-dependent, growth-promoting social emotional matrix that facilitates the emergence of the highly adaptive human functions of mutual play and mutual love. In the final section, I discuss the clinical applications of this interpersonal neurobiological model of intersubjectivity, which has a long history in the psychotherapy literature. Toward that end, I offer very recent paradigm-shifting hyperscanning research that simultaneously measures both the patient and therapist during a psychotherapeutic interaction. Using the Trevarthen’s two-person intersubjective model, this research demonstrates changes in both brains of the therapeutic dyad and the critical role of nonverbal communications in an emotionally-focused psychotherapy session. These studies specifically document interbrain synchronization between the right temporoparietal junction of the patient and the right temporoparietal junction of the clinician, a right brain-to-right brain nonverbal communication system in the co-constructed therapeutic alliance. Lastly, I discuss the relationship between the affect communicating functions of the intersubjective motivational system and the affect regulating functions of the attachment motivational system. (shrink)

This article is the second step in our research into the Symbol Grounding Problem (SGP). In a previous work, we defined the main condition that must be satisfied by any strategy in order to provide a valid solution to the SGP, namely the zero semantic commitment condition (Z condition). We then showed that all the main strategies proposed so far fail to satisfy the Z condition, although they provide several important lessons to be followed by any new proposal. Here, we (...) develop a new solution of the SGP. It is called praxical in order to stress the key role played by the interactions between the agents and their environment. It is based on a new theory of meaning—Action-based Semantics (AbS)—and on a new kind of artificial agents, called two-machine artificial agents (AM²). Thanks to their architecture, AM2s implement AbS, and this allows them to ground their symbols semantically and to develop some fairly advanced semantic abilities, including the development of semantically grounded communication and the elaboration of representations, while still respecting the Z condition. (shrink)

How does cultural knowledge shape the development of human minds and, conversely, what kind of species-specific social-cognitive mechanisms have evolved to support the intergenerational reproduction of cultural knowledge? We critically examine current theories proposing a human-specific drive to identify with and imitate conspecifics as the evolutionary mechanism underlying cultural learning. We summarize new data demonstrating the selective interpretive nature of imitative learning in 14-month-olds and argue that the predictive scope of existing imitative learning models is either too broad or too (...) narrow to account for these findings. We outline our alternative theory of a human-specific adaptation for ‘pedagogy’, a communicative system of mutual design specialized for the fast and efficient transfer of new and relevant cultural knowledge from knowledgeable to ignorant conspecifics. We show the central role that innately specified ostensive-communicative triggering cues and learner-directed manner of knowledge manifestations play in constraining and guiding selective imitation of relevant cultural knowledge that is both new and cognitively opaque to the naive learner. (shrink)

Artificial Intelligence (AI) pervades humanity in 2022, and it is notoriously difficult to understand how certain aspects of it work. There is a movement—_Explainable_ Artificial Intelligence (XAI)—to develop new methods for explaining the behaviours of AI systems. We aim to highlight one important philosophical significance of XAI—it has a role to play in the elimination of vagueness. To show this, consider that the use of AI in what has been labeled _surveillance capitalism_ has resulted in humans quickly gaining the capability (...) to identify and classify most of the occasions in which languages are used. We show that the knowability of this information is incompatible with what a certain theory of vagueness—_epistemicism_—says about vagueness. We argue that one way the epistemicist could respond to this threat is to claim that this process brought about the end of vagueness. However, we suggest an alternative interpretation, namely that epistemicism is false, but there is a weaker doctrine we dub _technological epistemicism_, which is the view that vagueness is due to ignorance of linguistic usage, but the ignorance can be overcome. The idea is that knowing more of the relevant data and how to process it enables us to know the semantic values of our words and sentences with higher confidence and precision. Finally, we argue that humans are probably not going to believe what future AI algorithms tell us about the sharp boundaries of our vague words unless the AI involved can be explained in terms understandable by humans. That is, if people are going to accept that AI can tell them about the sharp boundaries of the meanings of their words, then it is going to have to be XAI. (shrink)

The symbol grounding problem (SGP) proposed by Stevan Harnad in 1990, originates from Searle’s “Chinese Room Argument” and refers to the problem of how a pure symbolic system acquires its meaning. While many solutions to this problem have been proposed, all of them have encountered inconsistencies to different extents. A recent approach for resolving the problem is to divide the SGP into hard and easy problems echoing the distinction between hard and easy problems for resolving the enigma of consciousness. This (...) however turns out not to be an ideal strategy: Everything related to consciousness that cannot be well-explained by present theories can be categorized as a hard problem which as a consequence would doom the SGP to irresolvability. We therefore argue that the SGP can be regarded as a general problem of how an AI system can have intentionality, and develop a theoretical direction for its solution. (shrink)